By Andy May
This post is inspired by an old post on the CERES cloud data by Willis Eschenbach that I’ve read and re-read a lot, “Estimating Cloud Feedback Using CERES Data.” The reason for my interest is I had trouble understanding it, but it looked fascinating because Willis was comparing CERES measured cloud data to IPCC modeled cloud feedback. I love obscure, back-alley comparisons of models and data. They tend to show model weakness. I learned this as a petrophysical modeler.
Willis wrote the post as a response to a paper by Paulo Ceppi and colleagues on cloud feedback in global climate models (Ceppi, Brient, Zelinka, & Hartmann, 2017). We’ll refer to the paper as Ceppi17. I took the time the last few days to understand Willis’ post and Ceppi’s paper and this is what I figured out, let me know what you think in the comments.
In Ceppi17, N = F + λΔT. N is the energy flux imbalance at the top of the atmosphere, F is a forcing, in W/m2 due to a sudden increase in greenhouse gases. The hypothetical situation used in the paper was a quadrupling of the CO2 instantly, relative to preindustrial conditions. Then they calculated a hypothetical F. “λ” is the cloud feedback and ΔT is the total global temperature change required to regain equilibrium, or an N of zero. Their feedback numbers cannot be duplicated with data due to the implausible scenario. Here are two more versions of the equation for reference.
ΔT = (N-F)/ λ or λ = (N-F)/ ΔT
What is N? N is a force imbalance between incoming (or downward) radiation and outgoing radiation at the top of atmosphere, which we will define as the CERES satellites. N is positive if the downward force is larger (warming) and negative if the outgoing radiation is larger (cooling). The Earth is at equilibrium if the feedback, N and F are zero. Positive feedback (λ) leads to warming and a larger imbalance (N). The higher the feedback, the greater the warming. If the feedback is negative, cooling or slower warming is the result.
“CRE” is the cloud-radiative effect, or the difference between the clear-sky and all sky radiative flux at the satellite (TOA). Clouds reflect incoming shortwave solar radiation (SW), so more SW travels up to the satellite in the presence of clouds, on average the increase is about -45 W/m2. This is a negative number because it means more radiation is leaving Earth, a cooling effect. Clouds also block some outgoing longwave infrared radiation (LW) emitted by Earth’s surface, on average about 27 W/m2, a positive number, since it is energy retained by Earth or less energy reaching the satellite, a warming influence. The difference is -18 W/m2, which means, overall, clouds cool the earth.
One would think that the more clouds, the more rapidly the earth would cool, but it isn’t that simple. Some clouds, especially low level clouds and cumulus clouds tend to reflect more energy during the day than they trap during the night. High level clouds, like cirrus, tend to allow solar SW through and trap a lot of upwelling LW, thus they have a warming effect. So cloud type matters.
Figure 1 is a map of the average TOA (top of the atmosphere) cloud-radiative imbalance (CRE) at the CERES satellites. The blues are a negative energy imbalance or a cooling CRE. The map is an average of CERES monthly data from 2001 through 2019. The CERES variable mapped is “toa_cre_net_mon” or the “Top of The Atmosphere Cloud Radiative Effects Net Flux.” The effect is negative (or cooling) everywhere, except over deserts and the polar land regions. These are areas where the clouds tend to trap surface and lower atmosphere infrared and simultaneously allow solar shortwave radiation through to the surface, this combination creates a positive CRE and strong warming.
The point where the cloud warming and cooling effects meet in the Figure 1 color scale is where the lightest blue meets the light yellow. Right at zero is where the incoming energy equals the outgoing energy, with respect to clouds. Thus, except for the Sahara, the Middle East, Western China, parts of Southeast Asia, Indonesia, Northern Australia, the Southwestern U.S., and Mexico, clouds cool the earth. The darker areas in Figure 1 have more persistent clouds.
Figure 2 has lighter colors for clouds and darker colors for clear skies. Thus the lighter streak, near the equator, in both the Pacific and the Atlantic, is white in Figure 2, opposite of Figure 1. This the Intertropical Convergence Zone (ITCZ) where the trade winds of the Northern Hemisphere and Southern Hemisphere converge. This is where evaporation of seawater is at a maximum. Water vapor is less dense than dry air so it is a zone of rapidly rising humid air and frequent rain and thunderstorms. It is almost always cloudy. The ITCZ follows the Sun’s zenith point and the cooling effect of the clouds in this zone is very high.
The maximum cloud cooling, or the most negative CRE values, are in the small white spots in the middle of the black spots off of southern Peru and in southeastern China, north of Vietnam. These CRE values are very negative (extremely cooling) and off-scale. Figure 1 correlates reasonably well with the cloud fraction in Figure 2, or the lighter colors in Figure 3, with the exception of the polar ice caps.
Figure 3 is the NASA blue marble with ice and clouds shown in a Mercator projection. Notice the similarity with Figure 2, except at the poles.
Figure 4 shows the same data, the CERES EBAF 4.1 variable “toa_cre_net_mon,” as yearly global averages. EBAF means energy balanced and filled. As Norman Loeb and colleagues (NASA Langley Research Center) explain, Earth’s energy imbalance is so tiny, between 0.5 and 1 W/m2, that it is only 0.15% of the total incoming and outgoing radiation. Thus, the number we are looking for is the difference between two large numbers and barely above the uncertainty in the satellite measurements.
The calibration uncertainty in the CERES SW measurement is 1% and 0.75% for the LW. Thus the outgoing LW is only known to ±2 W/m2. There are many other sources of error, and as Loeb, et al. explain, the net imbalance from the standard CERES data products is only ~4.3 W/m2, not much larger than the expected error. Due to the coarse resolution of the CERES instrument, there are a lot of missing grid cells in the one-by-one degree latitude and longitude grid used to make the maps in Figures 1 and 2. To get around these problems Loeb and colleagues use a complex algorithm to fill in missing values and adjust the SW and LW TOA fluxes, within their uncertainty ranges, to remove inconsistencies between the global net TOA energy flux and the heat storage in the earth-atmosphere system (Loeb, et al., 2018).
The CRE, or cloud radiative imbalance value varies a lot from year to year, the average value over the 19 years is -19.1 W/m2, very close to the Ceppi, et al. value of -18 W/ m2 (Ceppi, Brient, Zelinka, & Hartmann, 2017). This suggests that total cloud cover is the main factor, it is shown below in Figure 5. As we would expect, as the cloud fraction goes down, the cooling effect decreases and the CRE becomes less negative. As the cloud fraction goes up the cooling effect increases.
In Ceppi17 a more positive feedback parameter (λ) implies warming. Since they are working with models, they can compute λ by dividing the computed forcing required to counter the original forced energy imbalance, due to clouds, by the resulting temperature change (ΔT). Figure 6 shows Ceppi17’s feedback globally due to clouds.
The units are W/m2/K, where K (Kelvin) is degrees C of warming or cooling due to clouds over the time it takes to reach equilibrium. Figure 6 is cloud feedback and not the same as CRE, but according to Ceppi17, cloud feeback tends to be positive and it suggests that clouds, over the long term, warm Earth and do not cool it. This made Willis question the whole paper. As he points out, Figure 6 is a plot of model output and Figure 1 is data. The data in Figure 1 is massaged and it is close to the edge in terms of uncertainty, but it is data.
Ceppi17 is lucky we cannot derive their feedback parameter from real data, because if we could, I suspect the map would look very different from Figure 6. For example, one of the places where clouds cool the surface the most is offshore of Peru, how does that turn into an area with a positive feedback? The other is southeastern China, OK, we get a little blue there, but nothing like what the actual data shows us. The very cloudy ITCZ is a very hot area in Figure 6, how do you do that?
I agree with Willis, this whole idea that clouds are a net positive (warming) feedback, makes no sense. The worst of it is that nearly every model uses a positive cloud feedback. Cloud feedback is the largest component of the model-computed ECS (the temperature sensitivity due to a doubling of the CO2 concentration) that the IPCC prefers. As we know, clouds cannot be modeled, and must be parameterized (the fancy modeling term for “assumed”). As Steve Koonin’s upcoming book, Unsettled, reports, scientists from the Max Planck Institute tuned their climate model by targeting an ECS of about 3°C by adjusting their cloud feedbacks. He adds “talk about cooking the books.” (Koonin, 2021, p. 93).
Ceppi17 reports that cloud feedback is, “by far, the largest source of intermodel spread in equilibrium climate sensitivity (ECS).” They also point out that cloud feedback is strongly correlated with model derived ECS and supply us with the data, it is plotted in Figure 7.
Oops! Clouds cannot be modeled, models assume their clouds have a warming effect, CERES says clouds have a net cooling effect, a large net cooling effect of -18 W/m2. The models say the entire human influence on climate since the beginning of the industrial era is 2.3 (1.1 to 3.3) W/m2 (IPCC, 2013, p. 661), which puts the cloud impact of -18 W/m2 into perspective. Notice that the variability in Figure 4 is larger than 2.3 W/m2. How much of the ECS from models is due to their assumption that clouds are net warming? How much is due to their assumption that ECS is 3 W/m2? So many questions.
Willis Eschenbach kindly reviewed this post for me and provided valuable input.
Works Cited
Ceppi, P., Brient, F., Zelinka, M., & Hartmann, D. (2017, July). Cloud feedback mechanisms and their representation in global climate models. WIRES Climate Change, 8(4). Retrieved from https://onlinelibrary.wiley.com/doi/full/10.1002/wcc.465
IPCC. (2013). In T. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. Allen, J. Boschung, . . . P. Midgley, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press. Retrieved from https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_SPM_FINAL.pdf
Koonin, S. E. (2021). Unsettled: What Climate Science Tells us, What it doesn’t, and why it matters. Dallas, Texas, USA: BenBella. Retrieved from https://www.amazon.com/dp/B08JQKQGD5/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1
Loeb, N. G., Doelling, D., Wang, H., Su, W., Nguyen, C., Corbett, J., & Liang, L. (2018). Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product. Journal of Climate, 31(2). Retrieved from https://journals.ametsoc.org/view/journals/clim/31/2/jcli-d-17-0208.1.xml
There seems to be enough overlap to combine this work with Willis’ into a larger study on how to correctly compute warming.
It is more of why computer models do not deal with clouds correctly. Which is a large enough effect to explain why the GCM’s are fantasy.
Andy, I covered similar territory back in 2014 in ebook Blowing Smoke essay Cloudy Clouds. Not much has changed since.
If you work thru IPPC using Monckton 2016? and Dessler 2010 (previous posts) you discover clouds are about net zero feedback. Regards.
Rud, I don’t think so. The data suggests they are negative on average.
No one knows for sure, but I think low-level clouds are net negative, they reflect more than they trap. The cloud tops are not at a very different temperature than the surface. High-level cirrus can be positive, but they are only important in desert regions. And, as Lindzen showed, they are quite sensitive to surface temperature in the tropics.
I know of some research that is being done right now that should explain this. The IPCC is wrong, as I explain in the post.
Low clouds are a large negative feedback despite what various references might imply due to averaging 2/3 cover over day and night, and extrapolating clear sky measurements, especially when they cover horizon to horizon, and even high thin clouds are really only positive feedback because of how much sunlight they let through during the day. Hartmann’s Global Physical Climatology, Fig. 3.20 is a good reference, and the following graph freely downloadable by Corti and Peter “A simple model for Cloud Radiative Forcing” gets the idea across.
Basically the planet’s oceans, albedo=.06, absorb sunlight and generate water vapor and low clouds, and keeps doing this until the planet’s Albedo=.304, at which point daily heat IN and OUT balance. 100% cloud cover would give the planet an albedo of .8 instead of .3 and be much colder.
Most clouds are below 6 km and have optical depth over 4, the lower right hand corner of the graph.
As I have demonstrated previously, an average albedo of 0.06 is too low.
He’s probably correct if we lived on discworld. Where it is perpetually noon and the sun is directly overhead from dawn to dusk. Clouds are also not diffuse.
I am seriously considering moving to the Discworld. At least no one there will try to take away my cats and magic actually works…sort of….
If you were living in Granny Weatherwax or Nanny Ogg territory, someone there might “borrow’ one of your cats now and then. It might be a significant privacy concern, really.
https://tvtropes.org/pmwiki/pmwiki.php/Fridge/AHatFullOfSky
Agreed, a calm water surface is more reflective out near the horizon and has a higher albedo, but 20 foot high waves not so much. I admit to choosing the lower end of the scale to emphasize the difference in local Albedo between sea and cloud at mid-day when the real heat exchange happens.
The reflectance of water is very complex. Internal diffuse reflectance occurs from suspended sediments, most strongly where rivers enter the ocean, and where waves stir up sediments along the coast. Internal reflectance also occurs from plankton suspended in the water column. In both cases, the internal reflectance is inversely related to the specular reflectance, which controls how much light can enter the water. Surface roughness re-directs the sheet specular reflectance and the glint may actually be higher for a slightly rough surface with nadir illumination. Very rough surfaces can support total internal reflectance with 100% reflectivity. However, the apparent surface roughness decreases as the angle of inclination increases to near the glancing angle. One can actually observe specular reflection from a plowed cornfield with stubble and clasts of sod. Yet, that same plowed corn field will be a very good diffuse reflector near noon!
“. . . and the glint may actually be higher for a slightly rough surface with nadir illumination.”
Your major points are good, and I was following you up to that statement. Did you mean to say “zenith” illumination instead of “nadir” illumination?
Thanks!
clouds being positive or negative contributors depend on at least the following,
Altitude, time of day, time of year, latitude, prevailing wind relative to poles/equator, etc. so simple areal metrics or whatever are likely to fail.
Where I live we get late afternoon cool sea breezes which stop often late in the evening with cloud cover and a warming evening. Model that if you can, because we can’t even predict it on a day-by-day basis.
You need to remember how clouds got there in the first place.
A massive transfer of energy from the surface to cloud level.
“we would expect, as the cloud fraction goes down, the cooling effect decreases and the CRE becomes less negative. As the cloud fraction goes up the cooling effect increases.”
Your data appears to show this, and I have seen sunshine data trends that show most of the recent decades warming is the result of increased surface solar radiation.
However I think your net cloud cooling increases even further when global oceans are considered. It is often noted that the oceans store 1,000 times more energy then the atmosphere. ( In affect they are a very large battery for stabilizing and warming our climate) All positive ( warming) or negative
(cooling) affects on our planet’s system depend on the residence time of the energy input. Clouds increasing albedo shorten the residence time of SW insolation. Sometimes GHGs increase the residence time of LWIR surface radiation.
When clouds prevent SW insolation from reaching the oceans, they are also preventing energy input into the longest residence time energy storage facility on earth, our oceans.
So some of that insolation, when it occurs, is not immediately reflected by any measurement of outgoing radiation. A portion of that energy penetrates below the ocean surface ( up to 800 feet deep) and is lost to the atmosphere for days, weeks, months even years.
So a certain portion of outgoing LWIR is energy coming from days, weeks, months, and years of prior ocean received insolation.
This is part of the very fine radiative balance that our atmosphere us in.
This takes us back to your sentence ” As the cloud fraction goes up the cooling effect increases.”. As some of that energy is no longer entering the ocean energy storage system, the cooling affect is greater then the incoming – outgoing data shows. Over time an increase in clouds would reduce the heat balance of our oceans energy below surface storage.
“These are areas where the clouds tend to trap surface and lower atmosphere infrared and simultaneously allow solar shortwave radiation through to the surface, this combination creates a positive CRE and strong warming”
This must be the most insanely stupid statement I have read for quite a while. Do you really think there are regions(!) where clouds are largely transparent for sun light, but opaque for LWIR? And then regions where it is the opposite? I mean, I know these data are confusing because they are simply wrong and I am going to clean up the mess on my upcoming site. But this way of “making sense of it” is just ludicrous.
OK, clearly you feel strongly about this. However, where is the evidence to support your claim.
No, I was just drunk. LOL
But it is true, the statement is stupid and it obviously makes no sense. The problem is you put these “satellite data” on a shelf and pray to it, as if they were almighty. But rather they are low quality products based on simplifications and assumptions that hold no water. At best these data should be ignored, unless you understand the underlying issues. Which btw. I posted already somewhere in the comments on this site. Again, I see the problem, people need time to understand and so I will have to deal with it more profoundly.
On the other side some people are so proud over the fact they can retrieve “satellite data from NASA”, they are getting goosebumps over it. They want these data to be significant. Without them the following statement still holds true:
“In short, the fundamental question, whether clouds cool or warm the climate has remained unanswered.”
https://www.researchgate.net/publication/6060960_Cloud-Radiative_Forcing_and_Climate_Results_from_The_Earth_Radiation_Budget_Experiment
When you can’t win an argument attack the person
When you can’t believe the science, attack the data
If the data is so poor quality that you can’t use it to refute climate models, then why does NASA even bother to collect the data?
So the poor quality data is so poor it finds exactly the OPPOSITE of what the climate models say? Who exactly is praying to what god here?
E. Schaffer, The idea that most upper-level cirrus clouds are more transparent to incoming solar shortwave radiation than they are to outgoing infrared is controversial, but well known. I refer you to Richard Lindzen’s excellent recent review paper: “The Iris Effect: A Review.” 19 March 2021 Asia-Pacific Journal of Atmospheric Sciences, https://link.springer.com/article/10.1007/s13143-021-00238-1
But what about the Solar LWIR?
On a high up “hazy” day you can still feel the difference in sunshine reaching the earth, so it must be doing something.
AC, clearly it is, and over the oceans it is preventing deep energy penetration into the oceans. Some of that lost incoming energy would not be reflected in CRERS data if it instead reached the oceans, as it would be lost to the atmosphere for a time regardless.
Well, it is true cirrus clouds are warming. But please skip the idea of selective transparency because it has nothing to do with it. Cirrus clouds are warming because of their altitude, or their very low emission temperature respectively. The higher up, the more clouds reduce emissions, the stronger their GHE so to say. And generally the GHE of clouds is massively underestimated by “satellite data”.
Andy
Thanks for the very informative article.
But I’m still confused.
Does more CO2 actually lead to more or less clouds(timing, type, height, location)?
What is the actual mechanism CO2 drives that makes more or less clouds in each region?
For example – Does extra CO2 force the Indian Ocean Dipole to make more or less clouds in either Africa or Australia?
It is my understanding that the IPCC has almost zero quantitative data to prove more or less clouds from extra CO2
Thanks in advance
Waza, I don’t know of any direct connection between CO2 and clouds. Clouds do respond strongly to changes in surface temperatures though. Surface temperatures respond to the net energy flux. If incoming energy is higher than outgoing, the temperature goes up and vice-versa. If CO2 directly causes warming it is very slight, perhaps 1 degree per doubling (ECS=1). Thus, the warming feedback is critical. There is an easily understood relationship between water vapor (a much stronger greenhouse gas than CO2) and temperature, so the modelers use that. But the relationship between cloud feedback and temperature (the subject of my post) is even stronger than water vapor, but very poorly understood, so it must be assumed. Modelers always focus on the simple stuff because they can’t do anything with the complex stuff, like clouds. My point is, they are modeling the elephant’s foot and ignoring the elephant.
Andy
Thank you for confirming my suspicions.
Andy,
Please let me state my mostly unverifiable opinion.
At top of troposphere CO2 is 400 ppm, used to be 280. Thus TOT now more efficiently radiates to outer space, so TOA is a little colder than it was a century ago. At about 7km, water vapour and CO2 are both about 400 ppm, and there is sufficient optical depth above that not as much as TOT emitted IR makes it to outer space. So the 120 ppm of extra greenhouse gas (water 400 plus CO2 400 but used to be 280) causes mid-troposphere to be a bit warmer and radiate more heat both upwards and downwards. At low troposphere, water vapor dominates so much that 120 ppm extra of CO2 is irrelevantly small.
So the net effect of CO2 is really just to cause the mid-troposphere cloud tops to be a little higher elevation, thus a bit cooler due to lapse rate…thus a little less cloud top LW radiation escapes the atmosphere, causing a wee bit of global warming…. the cloud cover itself probably attenuating the often stated 2 or 3 degrees by maybe a factor of 2/3.
I have read Ceppi´s paper a couple of times. I think they are doing something very strange.
When they talk about cloud feedback they are mixing two things.
They state that there is a positive cloud feedback at constant cloud fraction.
The logic is like this – the height of the troposphere increases when CO2 increases -> top of anvil clouds will reach a higher altitude -> top of anvil clouds will be cooler and thus radiate less.
This effect will cause additional warming.
They still say that an increased cloud fraction will cause cooling.
There is one positive effect (increased height of cloud top) and one negative effect (increased cloud fraction).
They do not clearly separate these two effect, but rather lump them into one parameter (cloud feedback).
A modeler thus have two nice parameters:
Had an argy bargy with another reader on the syntactical and logical coherence of this type of thought pattern. This quote of yours makes my point easier to illustrate.
“Yo, mister climastrologist, the top of the farkin’ cloud is cooler, specifically because it radiated so effing much already, twerpface!” Trapping the friggin’ heat by non-radiation, my word!
Thank you for highlighting that specific phrase for me, my mind can redeploy that section on other thoughts.
Ok.
I do not make this statement. Ceppi does.
Just trying to explain why Ceppi says that the cloud feed-back is positive, while the CERES data shows a negative feedback.
Ceppi´s positive cloud feedback comes from “top of anvil clouds will be cooler and thus radiate less.” and has nothing to do with the cloud fraction.
My view ? I think that Ceppi´s statement about increased height of the troposphere is highly questionable.
In fact, the vast majority of the GHG effect comes from “increased height of the troposphere”. Does the height increase ? I have no idea. .
To be clear, I thanked you for quoting the stupid bastards, because it crystalised an internal argument for me. Spent a week trying to line those duckies up, and there you gone dunnit!
P.S. I thought I presented a concise and apt answer to their “downwardly forced radiation due to cooler top” nonsense. Ah well…
…Imagining what a “twerpfaced climatologist” would look like… and Michael Mann’s face “fills the entire poster”.
Jonas and paranoid, Good discussion and it illustrates a very good point. The modelers, like Ceppi, live in a cartoon world without color. High-level clouds are cooler, but they aren’t static! The tropopause moves up when temperatures are higher, but down when they are cooler. Things change minute to minute, but we don’t know the equation or the parameters for the velocity of the changes. The modelers must work with static averages, I think that is why they get it wrong.
Then there are the CERES observations that say they are wrong. Never forget the obvious.
Hi Andy,
Not 100% clear to me.
CERES shows that clouds cool the earth (that is clear to me).
Questions:
That is the question, just because the clouds have gone higher, because the clouds & the atmosphere are both warmer does not mean that they radiate any less energetically than when they and the atmosphere are cooler, but lower.
Ok, I think we have the same view.
Just want to state that we do not know that the clouds have gone higher. Or do we ?
I think it is an unverified hypothesis in the climate models.
Neither do we know if they radiate less today than 50 years ago.
It is all in a theoretical model that is not verified.
For some strange reason people believe this theory. Maybe it is right. Maybe it is wrong. We do not know.
By the way – thanks for an excellent article.
The attached chart shows the ToA response to atmospheric water. For July, the water has a strong cooling relationship with higher values TPW; 4W/sq.m/cm of TPW. The little kick at the end is the action over the tropical warm pools.
From Aug19 to July 20, there were 9 months where the slope was positive and three months where the slope was negative. For the twelve months the slope was positive at 1.4W/sq.m/cm.
Water is a net cooling agent in the atmosphere.
Using the term water vapour is where the problem starts. Ice in the atmosphere has a very large role, high absorption and high reflectivity – albedo trumps absorption.
Thanks Will, I had not seen that before.
I was having this argument with Richard Black formerly of the BBC back in 2009 (ish).
Not in as much detail, I might add.
Nothing has changed in the intervening years
Stunning! Cloud feedback vs ECS. As we know flights stopping over the US after 9/11 caused an increase in surface temp (less clouds), we also have the cosmic ray/cloud/surface temp mechanism, so it makes sense.
And with that the whole global warming theory is shot dead. Mind you the lack of WV increase over land killed any possibility of +ve VW feedback, so now it is doubly dead.
Temp increase after 9/11 was a complete coincidence caused by high and low pressure fronts moving across the continent. Check the continental US weather forecasts the day the flights departed.
As I squint against the African sun on a cloudless day, and I hear the hum of the solar-driven pump, a thought arises:
On many a cloudless day, my power meter tells me I lose half or more energy, and the sun looks sorta wan. This does not last forever, passes by/ dissipates/ shifts dimensions. I assume it is moisture content, but with no condensation, yet the effect on my silicon panels is the same or worse than a single layer of cloud, which often robs me of less than 10% power.
Maybe clouds are not as rigorously catalogued as we like to think? Water absorbing selected wavelengths? Invisible spirit clouds? Wazzap?
It’s true, the effect of clouds on climate is incredibly complex!
Sorry to go off topic.
A prolonged drop in solar wind speed in early April affected the weakening of the south polar
vortex.
Andy,
I have only read the abstract of Ceppi17 but I assume that in the papers cited in it is G.L.Stephens 2005,”Cloud Feedbacks in the Climate System:a Critical Review” in Journal of Climate 2005, and subsequent papers by him.
In “Taxing Air:Facts and Fallacies about Climate Change” by the late Professor Bob Carter the following appears in the Question and Answer format-
“The Sun obviously warms the Earth, but what cools it?-
…A recent summary paper by Graeme Stephens and co-authors estimates that the fate of the incoming average 340 watts/m2 (100%) of solar energy at the top of the atmosphere is as follows:
75 watts/m2- (22%)- absorbed in the atmosphere.
165 watts/m2- (49%)- absorbed by the Earth’s surface.
100watts/m2-(29%)- reflected back to space by atmosphere & surface.
The atmosphere and Earth having gained heat through the absorption of 240 watts/m2 (71%) of incoming solar radiation now seek to restore the overall energy balance by emitting heat back to space.
Complex energy exchanges occur that involve back-radiation loops from the atmosphere including importantly clouds and greenhouse gases, but the ultimate result is that 240 watts/m2 of heat energy escapes to space as longwave radiation from the top of the atmosphere.
When added to the 100 watts/m2 of incoming solar energy that is directly reflected this escaping radiative energy balances the incoming energy ( 240+100= 340 watts/m2) and the overall planetary energy balance is sustained.
Thus the answer to the question posed is that the energy that is directed back to space by direct reflection (29%) and by radiation (49%+22%= 71%) is what cools the earth; and of the radiative loss more than half is energy emitted by atmospheric greenhouse gases, the remainder issuing from Earth’s surface.
In other words,and to a degree counter-intuitively, greenhouse gases help to both cool (by the radiation that they emit to space from the high atmosphere) and warm ( by the radiation that they emit down towards the lower atmosphere and surface) the Earth.”
Andy,forgive me for setting out climate change 101 material,but the simplicity of this explanation is attractive to people like me challenged by Ceppi 17.
I can then start absorbing your paper.
Is the summary accurate?
Herbert, what you’ve written is fine in general average terms. You’ve described a general model of the Earth’s energy budget. But the numbers are huge, relative to the difference humans might make, which is roughly 2 W/m2 per 150 years or so. So very small errors in any of those averages and the velocity of the changes in those numbers matter a lot. This was the point I was trying to make. Clouds change every day, even every minute, in altitude, optical depth, percent coverage, etc. They especially change in their reflectivity. The changes are huge, as shown in Figure 4.
But they can’t be modeled, so they are ignored.
Andy,
Thanks for your reply.
Your point is well taken as to the enormity of the figures,and the clouds aren’t able to be modelled.
As you remark to Bob boder, Lindzen is correct.
The human impact is exceedingly small and easily controlled by clouds.
Interestingly the uncertainty of clouds in modelling is confirmed by an unusual source.
Here is Gaia author and climate scientist James Lovelock in The Guardian on 29 March 2010-
“The great science centres around the world are more than well aware how weak their science is.
If you talk to them privately they’re scared stiff of the fact that they really don’t know what the clouds and the aerosols are doing.
They may be absolutely running the show. We haven’t got the physics worked out yet.”
Hear!Hear!
So if the models says clouds are the largest positive feedback and in fact they are negative then CO2 warming causes more clouds hence cooling. Wow sounds like a thermally balanced system! No wonder RGB said years and years ago, if we can have run away global warming why hasn’t it already happened?
That’s what convinced me maybe 20 years ago.
Bob, Correct. I think Lindzen is correct, and clouds are the balancing force or feedback. Clouds are extremely sensitive to temperature and increase or decrease their reflective properties, through changes in altitude and area to keep us in a narrow temperature range over the short term. The human impact is exceedingly small and easily controlled by clouds. But orbital variations are too strong for clouds to overcome, thus we have interglacials and glacials. CO2 is a pin prick, clouds are a knife, orbit is a broadsword.
So do us one on the orbit then! I would, but I’m way too lazy right now to find out where to begin. Orbital positions of every planetary body, moon and large comet for the past, say, three orbits of that furthest planet, erm, Pluto? Neptune? That one. Compare with climate cycles. Make graph. Astound and edify world with my cleverness…. wonder if there’s coffee? Yawn. Must. Verify. Sun’s. Centre. Pozzzzzzizzzzzshn… It Moves!!! Zzzzz…
“So if the models says clouds are the largest positive feedback and in fact they are negative then CO2 warming causes more clouds hence cooling.”
The alarmists don’t want to hear that! Moller claimed an increase in CO2 would result in net cooling of the atmosphere.
Every day, I thank the entity of life (whatever name individuals give to that deity) for the fact this site WUWT and a few other open sites exist, that give rise to considered scientific discussion and debate.
Now with a bit of luck, some of the previously open media channels like the BBC, CNN, ABC, CBC, etc, will one day reflect on their “settled science” position/belief, and actually allow some actual climate science discussion to be carried by their MSM.
On a personal note, re clouds.
I am still concerned about that butterfly in south America that is causing typhoons in Japan.
Now if we could only track it down, we would have complete control…..
“Every day, I thank the entity of life (whatever name individuals give to that deity) for the fact this site WUWT and a few other open sites exist, that give rise to considered scientific discussion and debate.”
Me, too. Especially where climate change is concerned because climate change is a very complicated subject encompassing many scientific disciplines and fortunately, WUWT has experts in all these areas, so when you get in a particular area you are not familiar with, you will find someone here who is familiar with it and will explain it to you.
The experts here put the Alarmist hyperbole about “climate emergencies” into the proper context and calm the fears of those uncertain about alarmist claims of coming CO2 disaster.
Feedbacks in the climate models are very common but in reality, positive feedbacks cannot be found in nature.
The warming since 2001 is mainly due to shortwave radiation anomaly. This anomaly had a maximum in 2019:
https://www.climatexam.com/single-post/temperature-increase-since-2016-is-not-anthropogenic
Now, this anomaly is decreasing and therefore the global temperature has dropped rapidly and is now back in the average temperature pause value of 1997-2014:
https://www.climatexam.com/single-post/global-temperature-dropped-to-the-pause-level-of-the-early-2000s
Antero,
You said “Feedbacks in the climate models are very common but in reality, positive feedbacks cannot be found in nature.”
Positive feedback has only to do with phase of a response to some excitation. All resonant system responses are due to positive feedback. System gain does not have to be greater than unity. Examples in nature are legion.
-BillR
Tell me one example.
The wind whistling through the pines. Branches swaying in the breeze. All turbulent flow in streams and oceans. Vortexes in tornadoes and hurricanes. Double layers in plasma. All structural resonance of any form whatsoever. Need I go on?
If branches way in the breeze, this swaying would increase, even though the breeze magnitude is the same. If this would be true, finally this swinging of branches would be so fast and furious that they would be cut off, even though the breeze magnitude remains constant. That will not happen.
The energy input is limited and the system gain is less than unity; therefore runaway does not occur. But, given enough input energy, branches DO come off the tree. Differential equations are taught in second year engineering math. All systems of 2nd or higher order exhibit positive feedback at some characteristic frequency. Pretty much everything exhibits resonance due to this.
All systems exhibiting chaos are due to internal positive feedbacks: weather, biology, Navier-Stokes equations, etc. All systems exhibiting fractal behavior have internal positive feedback. The beauty of these structures weren’t available before the advent of digital computers, but nature was there first.
-BillR
“The wind whistling through the pines. Branches swaying in the breeze.”
Winds are the result of swaying branches?
LOL.
In complex systems, it *is* often difficult to determine cause and effect. I cut my teeth on post-trip transient analysis of a certain nuclear power plant. Figuring out the root cause from integrated behavior is not for the faint of heart. But generally, if one keeps in mind the laws of thermodynamics and the laws of control theory, root cause is found.
-BillR
BillR,
Okay. Just to be clear, my admittedly flippant response was to your Nick Stokes-like response to AO. Specifically, just because wind can induce destructive motion in tree branches (and badly designed suspension bridges, while we’re on the subject of resonance), doesn’t negate AO’s inference that the net positive feedback (presumably from water vapor) built into climate models is problematic.
It’s been a while since I studied thermo, fluid mechanics and differential equations in my undergrad days, so I’ll respectfully defer to your expertise in these. However, you should consider the fact that Earth’s ability to maintain relative climate stasis over the past 525 million years (at least) in the face of Milankovitch cycles, plate tectonics and even asteroid strikes, is pretty solid evidence that the climate system operates under a regime of negative feedback.
And to your comment on climate stability, I wholeheartedly agree. And I also plead guilty to being overly pedantic.
One of the most interesting things about chaotic systems is the seemingly inherent stability, within the realm of fundamently uncertain behavior. When Edward Lorenz first discovered the issue, he coined the term “chaos” for the phenomenon. Later researchers used the term “strange attractor” to describe the inherently stable behavior of such systems.
My point is, I think, that the real world is incredibly complex, and bold blanket statements about this or that are rarely the whole truth. I actually love Willis’ theory of emergent behavior; it fits a whole lot of things that I have also personally observed.
Years ago, when I saw Willis’ initial foray into the subject, he showed a graph (as I recall) relating CERES TOA emission vs Sea Surface Temperature, or something like that. I thought, “Aha! Here’s a way to parametized clouds based on just the nature of this curve. It could much more accurately predict the spacial and temporal cloud response, even when thunderstorms, etc. can’t be modeled.”
Of course, I didn’t do anything about that at the time, but I thought that surely with all of the smart people in the room it was only a matter of time before such an obvious thing was done. Doing curve fits for modeled behavior is something I had done in successfully in real time control. One only needed a predictive model of the system behavior to create adequate anticipated feedback for enforcing control stability. It’s called “model predictive feedback” and it works, as long as that’s not the dominant feedback for long term control. Done correctly it simplifies the instrumentation requirements and also improves fault tolerance; which is just the thing needed for improving model accuracy with sparse data.
So, why isn’t it done? Or, if it is, why doesn’t it work? Are we so cynical that we build our climate models on expected behavior rather than first principles? I think a already know the answer to that.
-BIllR
Thanks BillR – very informative and very interesting.
Positive feedback is extremely common in Chemistry. A large-scale reaction can easily go out of control and become violent or even explosive if the heat of reaction is not evacuated quickly enough. This phenomenon is very well known to process chemists and chemical engineers.
I agree with Willis, this whole idea that clouds are a net positive (warming) feedback, makes no sense. – article
I would suggest that instead of being lab rabbits and working in a controlled environment, these scientists take the time to spend REAL time in the REAL world, outdoors on sunny days and away from cities (which are heat islands), out in the countryside where the sun does or does not shine, depending on weather conditions.
There is a noticeable drop in temperature when you drive from a clear sky environment into the path of an oncoming storm with clouds so densely loaded with water that they are nearly black. I’ve been through this more than once, and I’m sure that any OTR trucker can tell you the same thing. Those are the people I would listen to, not these lab rabbits who never leave their computers and rely entirely on buzzing electrons to do their “outdoors work” for them. That’s in the warm period usually referred to a Spring through Summer into Autumn.
Geezo Pete, there is a noticeable drop in temperature during a solar eclipse! How hard is that to figure out????? During the last one in my AO, I was lucky enough to have a camera that could handle the shots with no damage, and the FIRST thing I noticed was that the temperature dropped, stayed down, and then when the Moon moved away from the Sun, the temperature went back up to its previous level. How hard is that to figure out?
Maybe some day, someone will explain to me why none of these science people can bring themselves to go outside and observe the REAL world. They simply do not understand the real world at all.
I did not even read your rant! How dare you suggest we ignore the Settled Science? Did the Good Doctor Frauci not explain to you; animals carry disease, and humans should under no circumstances interact with wild creatures.
Now go take your cat in for an injection of one of those experimental gene manipulators masquerading as vaccines, before you catch one of them zoosnottic sicknesses.
Geeze Louise, the gall of some people; “go outside and work outdoors and away from the City” indeed! There’s bats there, don’t you know?
Sara,
you remarks are spot on.
The findings of science are only valid within that special domain, where you have your scientific instruments at hand and are able to use them. This is so self-evident it may be easily overlooked. Because, you would think, everything in this world, in the “reality outside”, may be subject to scientific scrutiny, isn’t it? So there are no limits to this “scientific domain”? I think that idea is an illusion. These limits are there. They are unavoidable and even very robust.
This is something people who can detach from science or think “out of the box” are very well aware of. It seems some scientists and their followers are not. So they fall into the trap you describe, and overreach with their ambitions and instruments. And in so doing seem to withdraw themselves in an artificial and mainly abstract virtual world.
One of the consequences of this attitude is the idea that a purely instrumental or technocratic approach will be our blessing. I don’t share that vision. I am intrigued by the success of science as a special and unique tool to do research. But this tool has its limitations, as has any tool. There are other useful tools and ways to go, still happily alive and available. One way to discover them indeed is just go outside and leave your agenda and computer for a while.
Andy, clouds are basically water in some form, both water and vapor. I never see any treatment on how the sun’s near IR, which water and water vapor absorbs a lot of, makes a difference. It seem to be dealt with by using the assumption that clouds “reflect” the sun’s energy, instead of absorbing any of it.
Almost 50% of the sun’s incoming energy is in near IR. H2O absorbs a good chunk of this both at the surface and in the air, including clouds. Water is not only warmed by LWIR and therefore some of the energy attributed to “back LWIR radiation” should really be classified as indirect insolation.
Where is the energy in the following diagram accounted for in any of this.
I don’t know. A lot of incoming solar radiation is in wavelengths that can be absorbed by water and water vapor. Of course, it is then re-emitted at a new wavelength dependent upon the local temperature. But how this is handled in the models, I’m not sure. At the satellite it would be LW outgoing radiation. The satellite would only see the reflected shortwave, not the cloud absorbed SW, later emitted as LW.
KISS principle can be applied here. The atmosphere absorbs about 30 % of incoming shortwave radiation due to clouds and GH gases (water vapor 77 %, ozone 20 %, and CO2 2 %). Once absorbed by the atmosphere, the atmosphere radiates it as infrared radiation to the surface (about 75 W/m2). Check the Earth’s energy balance.
But then CO2 “back radiation” is not near what it is portrayed as.
The total radiation, also called reradiation is about 395 W/m2. It is the sum of four different energy sources: SW absorption 75, LW absorption by GH gases and clouds 155, latent heat absorption 91, and sensible heat absorption 24 = 345 W/m2. GH effect totally 155+91+24 = 270 W/m2 and not 155 W/m2 as defined by the IPCC. This 155 W/m2 is really according to the IPCC definition – not Fourier, or Tyndall, or Arrhenius. The absorption by CO2 is only 20 W/m2. Then you can calculate, what is the contribution of CO3 in the GH effect = 100*20/ 270 = 7,5 % corresponding to 2.5 C degrees. Then you understand, why the IPCC has wrongly specified the magnitude of the GH effect.
Spectacular graphic and a good question.
Regardless, is there is a typographical error? Solar “Readiation” Curve.
Also, wavelength is misspelt.
Correct, clouds absorb solar near infrared, so the cloud albedo is not really as much as 30%.
As the oceans warm, surface evaporation increases, which moves more water vapor upward that condenses into more clouds that warms the local atmosphere, increasing longwave radiation to outer space, a cooling action. Should this be included in cloud feedback or treated as a new negative feedback factor?
Richard, good question, I don’t know. Clouds are both a forcing and a feedback. This whole forcing/feedback is nonsense in the real world, in my opinion. It is useful when programming the models because you’ve got to start somewhere. But, in the real world, everything affects everything else, so all the so-called “forcings” are feedbacks except for the incoming radiation from the Sun.
I thnk the theory is that CO2 increases heat. More heat would result in more moisture in the air. More moisture in the air would lead to an increase in cloud cover. NO?
Not a bad summary
Wait, so clouds have a warming effect where there’s least of them? That sounds strange. How about a better alternative:
Hot places allow little condensation to form clouds. Hottest places during sunshine control clouds, i.e. the deserts, or “bare land”.
Just a thought. Comments?
Willis,
Please use EBAF 4.2, not 4.1.
Links are on my blog. You know 🙂
Water vapor as a gas is very important because it raises the height of the tropopause. The higher the tropopause , the longer the lower vertical temperature gradient persists.
 
The graphic shows a lowered tropopause over northern Mexico. There the overnight temperature will drop quickly. In the western US we have a high that contains a lot of water vapor from the Pacific Ocean and there the high temperature will remain overnight.
The very low UV radiation compared to previous solar cycles indicates, a decrease in total solar radiation. The oceans are known to accumulate solar radiation, so a decrease in ocean heat can be expected.
https://www.iup.uni-bremen.de/gome/gomemgii.html
The problem with all models is the same as the problem with all politicians. And that problem is time. Over time, they all divert from reality. So when permanent politicians cite model results as justification for their policies, the result is actually the square of fantasy, which is what you are seeing now. And that’s the real emergency, because fantasy is not sustainable.
Europe: less air pollution = less aerosols = less clouds = more sun = higher temperature. This correlates with more co2.
hence co2 must be the only cause. Not.
Andy, is there an authoritative dataset for trends in global cloud fraction? I remember reading that cloudiness had gone down in recent decades, and that this had a warming influence.
Jit, as far as I know the data I used to make Figure 5 is the definitive dataset. It shows cloudiness increasing over the past 20 years, although it dropped a lot since 2016.
Thanks, I found this:
https://www.ssec.wisc.edu/news/articles/13122/
but it seems to show something quite different, so I’m a bit confused.
Cloud cover used to be manually estimated at weather stations in “Octs” or 1/8 of the sky. That’s likely why the spread in older data. Satellites improved this by counting white pixels on CCD screens, which are highly susceptible to someones interpretation of just how white a pixel has to be before it is really a “cloud”. There are also issues with how much IR radiation is reflected from multi-layer cloud cover and how much of it there is.
Probably mother nature doesn’t care…as the .06 albedo sea surface warms in the bright afternoon sunshine, she just cranks out more water vapor to make more clouds until the resultant planetary albedo is .304 again. As long as the Albedo is OK, she doesn’t care if the clouds are multi-layer, thunderstorms, 2000km weather fronts….all that is just random weather to her.
The reason for my confusion is that the figure at the link (global cloud cover anomaly) seems to vary by 4% over the last twenty years, while the figure in the head post (% cloud cover) varies by 20%. Not only that but to my eye there is no resemblance at all between the form of the two datasets.
The data linked to goes back to 1980 and is entirely from satellites so presumably the estimates are derived from brightness per pixel not manual classification.
“As we know, clouds cannot be modeled, and must be parameterized (the fancy modeling term for “assumed”). “
I think t would be better to describe the assumptions used for clouds in the models as fudge factors or GIGO factors.
I followed the posting right up until it jumped off into models. I agree, the models make no sense.
I did come up with an idea. I am wondering if it possible to separate the world into 4 time divisions – cloud feedback at noon (including +/- 3 hours), at 6PM, at midnight, and at 6AM. If clouds are really acting as heat transports one should see this represented in the percent of clouds over the Earth at various times of day. I hate this idea of a Global Temperature and a Global Cloud Cover as it seems to just simplify everything into “a miracle occurs here”. It’s like averaging a man and a woman and determining the average person is 48% male and 52% woman.
Just splitting it into daytime and nighttime gives one a much more informed view of cloud radiative effect…I like your idea…I think 6 zones would better….with noon and midnight +/- 2 hours being the most instructive, the others being more obviously intermediate cases than with 4 zones…make little Trenberth type diagram for each…finally add them up….etc.
Higher sea surface temperatures cause a decline in low cloud cover. So in a simple thermodynamic model, it looks like a positive feedback. But in the real world, ENSO and the AMO act as negative feedbacks to changes in the solar wind strength, and the cloud cover changes which they cause, amplify their negative feedback effect.
Such that stronger solar wind states in the 1970’s drove colder ocean phases and increased low cloud cover ,driving global cooling, and post 1995 weaker solar wind states have driven warmer ocean phases and reduced low cloud cover, driving global warming.
https://www.linkedin.com/pulse/association-between-sunspot-cycles-amo-ulric-lyons/
“Some clouds, especially low level clouds and cumulus clouds tend to reflect more energy during the day than they trap during the night. High level clouds, like cirrus, tend to allow solar SW through and trap a lot of upwelling LW, thus they have a warming effect. So cloud type matters.”
Surely at higher latitudes, winter low clouds would cause a net warming? What about the solar near infrared? that is absorbed by any clouds.
That’s not correct, most rainfall is at equator. Rain falls from clouds. SST is high there. SST is a little higher on either side of equator, but because of high cloud cover….
All clouds, including low ones, (actually especially low ones, but that will cause heads to explode) cause warming at night. All clouds reflect sunshine back into space during the day, especially thick ones, which are usually low. High thin clouds let more sunshine through, which is why they are assigned more “warming” effect. You are correct for the far North because there isn’t as much sunlight to reflect into outer space due to cos of zenith angle of incident sunlight, yet good IR transmission between the cloud bottom and the surface.
Yes, but by the same token, there cannot BE much downward radiation from such clouds, because they are not heated well by the sun, well, ’cause, you know, “cos of zenith angle”?
I have to ask: Has anyone actually measured this “down radiation” from clouds? In my universe, insulation explains all the heat under night time clouds, by disrupting convection, and it avoids the pseudophantasmagorigal reasonings thought up by those enforcing the ‘forcing’ paradigm. I climb up a high tower, and my eyes observe the complex stratification of the atmosphere. I read climastrology, and the unsubstantiated formulations and asumptionating makes my eyes water, crying for the total lack of appreciation modellers have for the varied beauty of real life existence.
Those poor buggers really need to get a life!
Higher SST’s do reduce low cloud cover, except for parts of the central tropics, and in the Arctic.
In the blog writing of mine, is a very illustrative figure (number 3), in which way the global temperature and the absolute water amount (TPW) have been developed from 1979 onward. The positive water feedback works well during the ENSO events but strange enough, at the same time the long-term feedback is going in another direction. You will not find these trends in any figures of climate establishment. You can figure out, why.
https://www.climatexam.com/2018
El Nino is a negative feedback, and the water vapour amplifies it. The WV trend is also a negative feedback because the warm AMO phase is a negative feedback to weaker indirect solar forcing, it’s warming since 1995 is also self amplified by the increase in water which it drives. The warm AMO phase reduces low cloud cover and increases surface wind speeds over the ocean, so more water vapour is generated, and the upper OHC also increases.
Interesting that over oceans, clouds always are negative feedback to varying extents
Over land, deserts and other arid lands clouds have positive feedback – however these are areas where clouds are atypical and I suspect most of the warming there is due to slowdown in nighttime cooling. The most positive feedback is over the Sahel (arid but not desert), Greenland and Antarctica. Some searching on “greenland climate” .. ~2 inches precip per year, “Greenland’s climate is … characterized by low humidity“, etc.
So semi-arid land areas, both hot and frigid, are where the strongest positive feedback exists.
I wonder why such large negative feedbacks are indicated in China, NW Pacific and SE Pacific off Peru/Chile coast. Even more so than the ITCG, where I would have expected to see the most negative feedbacks. And near neutral in the big Amazon and Congo rain forests was unexpected – but maybe due to some positive feedback in dry season offsetting negative feedback in wet season?
As a comment, an old flight instructor and professional pilot with over 38000 hours as pilot in command would sometimes relate his student’s observational experiences to those of us sober enough to listen. He had many students, some of whom were really talented aviators. Like sailors, they could live and die by misreading cloud formations and energy content in those wispy fluffy bundles of watery goodness the rest of us see as clouds. Willis has shared this type of observation from the ocean surface. Imagine a vaunted aviator taught by this older pilot. One of the most repeated reminder’s to his students was there are very few old bold pilots.
In the 1960’s with the advent of the turbojet engine many of these aviators were being told that t-cell anvil heads could only very seldom reach 50k ft.(maybe north of the 40th parrallel)
Some of these bright young pilots were relating to their mentor, how after leaving Beale AFB in sunny CA and refueling over the Pacific at 35000ft they would return to their cruising altitude of 60,000ft. Only about 11 miles above Willis but pretty much a world away in terms of perspective. A noticeable curvature at the horizon 600 miles distant a dark blue color to the sky not an almost flat horizon 6-12 miles away in a beautifal light blue sky like for Willis.
But like Willis they looked for clouds.
After several years of crossing the ITCZ numerous times they would become highly indignant when being informed by Air Force meterologists that anvil tops were restricted to at most 65K ft in the ITCZ. They would explain to their mentor that sometimes going up to the top of their aircraft’s operational altitude at 75 to 82k ft (they got pretty vague on actual altimeter readings) they would still be somewhat below the anvil tops. That was usually when the old, bold saw was drug-out and played. When they were so mission driven to attempt to traverse the clouds the amount of available but chaotic energy still in those clouds seemed to convince those younger aviators that their mentor was a very wise OLD pilot, if they got to share a beverage with him after that particular learning moment.
That lack of observational wisdom is a lot of what holds progress back in modelling our atmosphere, because modelling usually is under a dry roof in climate controlled quarters firmly anchores by gravity to terra firma like where most meterologist congregate.
Andy May, Willis Eschenbach, and that old flight instructor are three of my heros that at 2 years old might have stuck their fingers into electric sockets and survived a hazardous experience to learn there is always dangers in exploration and that it can be shocking to make bold assumptions. Thank you all for keeping up the good fight doing such good work and keeping an eye out for clouds.
Excellent point. Field work should be required for a degree in a physical science.
When the choice is between “the data” and a “lying leftist activist pseudo-scientist”… I never chose the leftist.
Clouds block sun and sunshine cannot “go around” the clouds. Heat can go around the clouds.
I question the entire feedback model proposed by the warmistas. Since the geologic record shows that most of the time the earth’s climate has been warmer than current, and the climate did not run away, obviously the feedback model only works over a very short temperature range if it applies at all. Since the fundamental prediction of the warm, humid layer in the troposphere predicted by the proponents of these models has been experimentally shown to not have developed, their entire model has failed its first and easiest prediction.
This strikes me as a very important result. If you run Fig 7 x axis out to -18 w/m2, what value do you get for ECS?
Looks to me like ECS goes negative.
ECS might be negative, in reality. But, positive or negative, it is a small number.
What correlation exists for cloud formation in relation to the level of cosmic ray flux? To that question I now would add formation of clouds at different levels? I could presume cosmic rays trigger far more upper level cloud.
Ewin,
I refer you to this report:
Svensmark, H. (2019). Force Majeure, The Sun’s role in climate change. GWPF. Retrieved from https://www.thegwpf.org/content/uploads/2019/03/SvensmarkSolar2019-1.pdf
They find correlation with low-level clouds.
Cloud cover? Is that it? I remember going to observe a lunar eclipse, the sun was setting on my back and I watched how the moon in front of me pulled clouds towards it, there was a strange warping effect on one of the images, it looked to me like a gravitational effect, but is that a thing? are gravitational forces accepted in science today? When you’re all arguing over a few tenths of a degree in a planetary anomaly or w/m2 do you really understand what’s actually going on?